SPECIFIC AIM 1: To identify aberrant expression of NF-kB regulators in ovarian cancer. Rationale: In a set of cancer samples, genes with an outlier expression profile are those with a dramatically high or low expression in a subset of samples. Outliers may indicate oncogenic events such as translocations, amplifications, or genomic deletions. Recently, a method to identify outlier genes was described, which relies on a scaling transformation of the expression data to accentuate extreme values. We modified this approach and applied it to multiple myeloma, attempting to focus on outliers associated with NF-kB activation. This approach identified extreme high expression of 2 oncogenes NIK and CD40, and very low expression of 3 tumor supressors TRAF3, CYLD and BIRC2/3 locus. These abnormalities occurred in myeloma cases with evidence of NF-kB activity, suggesting that the gain or loss of expression of these genes was causative. This approach has not been previously applied to the gene expression profiles of ovarian cancer, yet has the potential to identify diverse genetic abnormalities underlying the pathogenesis of the disease. Preliminary analysis of publicly available ovarian cancer datasets indicates that IGFBP2 is extremely under-expressed in the cases with highest IKKb signature gene expression. IGFBP2 negatively regulates cell growth in prostate and breast epithelia. Therefore one could hypothesize that the loss of IGFBP2 in ovarian cancer cells might allow growth-promoting effects of NF-kB cascades to ensue. Design: We will apply this method systematically to existing databases of ovarian cancer gene expression profiles (http://www.ncbi.nlm.nih.gov/geo/gds and internally generated data). In the initial phase, existing data will be analyzed and thus no additional investment, other than manpower, is required. Once outliers are identified, resources will be committed to classify and validate the target. Outliers will be correlated with the NF-kB signature expression as defined in our current work, as an estimate of NF-kB pathway activity in individual cell lines and patients. We will perform the analysis at decreasing levels of stringency, initially choosing a high cutoff for outlier gene expression to focus on cases most likely to have genetic abnormalities affecting mRNA expression levels. Extreme outlier expression of a known NF-kB regulator will prompt further investigation at the genomic and proteomic levels. We will quantify the genomic DNA by quantitative PCR in order to confirm gains or losses of the locus in question. We will attempt to investigate the gene product expression at the protein level by Western blot in the cell lines or with immunohistochemistry in tissue sections from the cases, as material and reagents are available. Experimental validation of the abnormality will be confirmed in ovarian cancer cell lines by either knocking down or overexpressing the gene, as appropriate. SPECIFIC AIM 2: To map out intersecting pathways that cooperate with NF-kB to drive the pathogenesis of ovarian cancer. Rationale: NF-kB activity is regulated directly by IkappaB kinases (IKKs). These kinases act downstream of signaling molecules that are known to be important in ovarian cancer including MAP-K, AKT, and TGF-beta. The stimulus for IKK activity, and the end result of each pathway, may be context specific. In the hematopoetic context, IKK-alpha activity has been most often described in the cytoplasm, as part of a hetero-trimeric complex regulating the activity of classical NF-kappaB components, or as a homo-dimer regulating alternative NF-kappaB transcription factors. In prostate cancer, however, IKK-alpha has a prominent role in the nucleus of the cell, de-repressing metastasis-promoting genes. In fibroblasts or macrophages, IL-1 activation can result in either classical IKK-beta cascades or alternative IKK-alpha signaling depending on the status of the IL-1 receptor associated kinase (IRAK). In non-malignant breast epithelial cells, TGF-beta is known to activate apoptosis;in the context of breast carcinoma, however, TGF-beta stimulates growth via IKK-beta that depends on TGF-beta-activated kinase binding protein 1 (TAB1). Therefore, the molecular context is key to determining which IKK is activated and how the signals will ultimately affect the cancer cell. In this Aim, we will seek to define the context in which NF-kB is activated in ovarian cancer, and the kinases that cooperate to propagate the signal. Such kinases might then be targeted in conjunction with NF-kB in order to tailor therapy for this subset of ovarian cancer. Design: Our work supported by the Marsha Rivkin Scientific Scholar Award established the sensitivity of a subset of ovarian cancer cell lines to a small molecule inhibitor of IKK-beta. We will use this inhibitor in combination with RNA interference (RNAi) targeting the human kinome to search for interacting pathways. We will conduct an RNAi genetic screen to uncover pathways that cooperate with IKK-beta in ovarian cancer. We will screen a library of small hairpin RNAs (shRNAs) targeting 500 protein kinases to identify genetic pathways that might potentiate or antagonize the toxic effect of the IKK-beta inhibitor. The ovarian cancer cell line, Caov3, will be transduced with a pool of retroviruses from this library and then treated with a submaximal lethal dose of IKK-beta inhibitor such that roughly 50% of the cells were killed after 7 days. Since each vector in the shRNA library possesses a unique 60-base pair molecular bar code sequence, we will be able to compare the complement of shRNA vectors present in cultures treated with the IKK-beta inhibitor to that in parallel untreated cultures. This will allow us to identify shRNAs that increase or decrease cell death in the presence of the IKK-beta inhibitor but ignore shRNAs that are toxic in a manner that is not synergistic with IKK-beta inhibition. Each identified kinase will be validated individually by shRNA knockdown in IKK-beta sensitive and insensitive cell lines;by small molecule inhibition, if available, to confirm synergy with the IKK-beta inhibitor;and by re-sequencing of exons to identify potential activating mutations especially in the kinase domain.